Evaluating the prognostic efficacy of biomarkers in pancreatic cyst fluid

Table 1 Characteristics of studies evaluating the diagnostic efficacy of cystic carcinoembryonic antigen and intracystic glycose for mucinous pancreatic cysts

Ref.	Type of study	Biomarker assessed	Patients included	Cut-off	Sensitivity	Secificity	AUROC
van der Waaij et al[24], 2005	Pooled analysis	CEA	450	< 5 ng/mL	50% (for PC, SCA)	95% (for PC, SCA)	-
				> 800 ng/mL	48%	98%
Thosani et al[25], 2010	Meta-analysis	CEA	376	-	63% (pooled)	88% (pooled)	0.89
Thornton et al[26], 2013	Meta-analysis	CEA	1438	-	63% (pooled)	88% (pooled)	-
Brugge et al[27], 2004	Multicenter study -prospective collection of data	CEA	341	192 ng/mL	73%	84%	0.79
Park et al[28], 2011	Single-center retrospective	CEA	124	200 ng/mL	60%	93%	0.89
Gaddam et al[29], 2015	Multicenter study, retrospective study	CEA	226	105 ng/mL	70%	63%	0.77
				192 ng/mL	61%	77%
Köker et al[31], 2021	Retrospective study	CEA	466	100ng/mL	-	-	0.930 (for differentiating LR-IPMNs from LR-MCNs)
							0.921 (for differentiating LR-IPMNs from HR-IPMNs)
kwan et al[33], 2024	Single center, retrospective	CEA	1169	20 ng/mL	89%	64%	0.80
				192 ng/mL	56%	78%
Rossi et al[32], 2024	Prospective observational multicenter study	CEA	50	192 ng/mL	55.6%	87.5%	0.65
		Intracystic glucose (glucometer)		50 mg/dL	93.2%	76.5%	0.74
Carr et al[36], 2018	Single center study -prospective collection of data	CEA	153	192 ng/mL	58%	96%	0.92
		Intracystic glucose (glucometer)		50 mg/dL	92%	87%	0.91
Gyimesi et al[38], 2024	Single center study -prospective collection of data	CEA	91	192 ng/mL	67.5%	97.5%	-
		Intracystic glucose (glucometer)		50 mg/dL	94.2%	81.3%	-
Gorris et al[39], 2023	Single center study -prospective collection of data	CEA	63	20 ng/mL, 192 ng/mL	80%, 50%	62%, 93%	-
		Intracystic glucose glucometer		50 mg/dL	100%	45%
		Laboratory		50 mg/dL	100%	60%
Smith et al[41], 2022	Multicenter - prospectively maintained database	CEA	93	192 ng/mL	62.7%	88.2%	0.81
		Intracystic glucose (laboratory)		25 mg/dL	88.1%	91.2%	0.96
Ribeiro et al[42], 2024	Single center, retrospective study	CEA	78	192 ng/mL	55.6%	87.5%	-
		Intracystic glucose		50 mg/dL	93.2%	76.5%	-
		Glucometer laboratory		-	-	-	0.870, 0.912
Williet et al[43], 2023	Multicenter study, retrospective	CEA	121	192 ng/mL	41.7%	96.9%	0.812
		Intracystic glucose (laboratory)		41.8 mg/dL	95.3%	91.2%	0.936
McCarty et al[44], 2021	Meta-analysis	CEA	609	-	56% (pooled)	96% (pooled)	-
		Intracystic glucose			91% (pooled)	86% (pooled)
Faias et al[45], 2021	Meta-analysis	CEA	5286	-	67% (pooled)	80% (pooled)	0.79
		Intracystic glucose	460		91% (pooled)	75% (pooled)	0.95
Zikos et al[35], 2015	Single center study -prospective collection of data	CEA	67	192 ng/mL	77%	83%	-
		Intracystic glucose	-	50 mg/dL	-	-	-
		Laboratory	-	-	95%	57%	-
		Glucometer	-	-	88%	78%	-
Faias et al[37], 2020	Single center study -prospective collection of data	CEA	82	192 ng/Ml	72%	96%	0.842
		Intracystic glucose (glucometer)		50 mg/dL	89%	86%	0.860
Simons-Linares et al[40], 2020	Single center study -prospective collection of data	CEA	113	192 ng/mL	50%	92%	0.78
		Intracystic glucose		41 mg/dL	88%	97%	0.95
		Laboratory		21 mg/dL	92%	92%	-
Guzmán-Calderón et al[46], 2022	Meta-analysis	CEA	506	-	61% (pooled)	93% (pooled)	0.861 (pooled SROC)
		Intracystic glucose			91% (pooled)	85% (pooled)	0.959 (pooled SROC)
Mohan et al[47], 2022	Meta-analysis	Intracystic glucose	566	50mg/dL	90.1%	85.3%	-
		All methods of measurement		-	90.5% (pooled)	88% (pooled)
		Glucometer		-	89.5%	83.9%

AUROC: Area under the receiver operating characteristic curve; CEA: Carcinoembryonic antigen; PC: Pseudocysts; SCA: Serous cystadenoma; LR: Low risk; HR: High risk; IPMNs: Intraductal papillary mucinous neoplasms; MCNs: Mucinous cystic neoplasms; SROC: Summary receiver operating characteristic.

Table 2 Molecular marker studies in pancreatic cyst fluid

Ref.	Type of study	Molecular marker	Patients	Sensitivity	Specificity	Accuracy	Conclusions
Khalid et al[51], 2005	Prospective single-center diagnostic study	KRAS codon 12, allelic loss, CEA, DNA quality	36	91%	93%	92.0%	KRAS followed by allelic loss is highly predictive for malignancy
Sawhney et al[52], 2009	Retrospective EUS-FNA study	KRAS, CEA, DNA quantity, allelic imbalance	100	82% (CEA), 77% (Mol)	-	-	CEA and molecular markers had poor concordance; combining improved sensitivity to 100%
Khalid et al[53], 2009	Multicenter prospective PANDA study	KRAS, DNA yield, LOH amplitude	113	-	KRAS 96%	-	Allelic loss and DNA quantity predicted malignancy
Nikiforova et al[54], 2013	Large retrospective cohort	KRAS codon 12	603	67% (IPMN), 14% (MCN)	100%	77%	KRAS highly specific for mucinous cysts, low sensitivity for MCNs
Singhi et al[55], 2014	Prospective surgical validation	KRAS, GNAS (codon 201)	91	65%	100%	82.5%	Highly specific for IPMNs; limited sensitivity for MCNs
Winner et al[56], 2015	Retrospective cohort study	KRAS, LOH, DNA content	56	50%	96%	73.0%	Molecular markers increased diagnostic yield, but less accurate than CEA
Rockacy et al[65], 2013	Retrospective prognostic study	KRAS	113	-	-		KRAS associated with poor clinical outcomes
Al-Haddad et al[66], 2015	Prospective multicenter IMP study	IMP (KRAS, TP53 + cytology/clinical data)	492	-	-	-	IMP outperformed Sendai guidelines in risk stratification
Springer et al[69], 2015	Prospective classifier study	KRAS, GNAS, TP53, SMAD4, LOH, BRAF	130	90%-100%	92%-98%	95%	Molecular algorithm reduced unnecessary surgeries by 91%
Jones et al[62], 2016	Prospective reclassification study	KRAS, GNAS, TP53, CDKN2A, SMAD4	92	86% (NGS)	100% (CEA)	93%	NGS reclassified cysts with normal CEA; detected high-risk lesions
Singhi et al[70], 2016	Clinicopathologic accuracy study	KRAS, GNAS, TP53, VHL, PTEN	225	100%	100%	100%	Outperformed AGA guidelines in detecting advanced neoplasia
Kadayifci et al[63], 2017	Retrospective validation study	CEA, KRAS, GNAS	197	86.2% (triple)	-	-	GNAS improved accuracy when added to CEA and KRAS
Rosenbaum et al[71], 2017	Retrospective cytology correlation	KRAS, GNAS, TP53, SMAD4	113	75% (cytology), 46% (late mutations)	-	-	NGS added value in identifying malignant cysts
Singhi et al[76], 2018	Large prospective validation	KRAS, GNAS, TP53, PTEN, PIK3CA	626	89%	100%	94.5%	High accuracy in cyst classification and risk stratification
Volckmar et al[59], 2019	Prospective biomarker study	KRAS, GNAS via NGS in cell fraction	22	100% (IPMN)	100% vs pseudocysts	100%	Mutations distinguished IPMNs from pseudocysts
Farrell et al[72], 2019	Cohort analysis with imaging features	KRAS, LOH, DNA amount	478	-	-	-	≥ 2 DNA abnormalities increased malignancy risk in cysts with worrisome features
Springer et al[75], 2019	Multimodal AI tool (CompCyst)	CompCyst (clinical + KRAS, GNAS, TP53)	862	-	-	-	Significantly improved diagnostic accuracy and reduced overtreatment
Laquière et al[73], 2019	Pilot NGS concordance study	KRAS, GNAS, TP53	17	78%	62%-100%	-	PCF and tissue mutations were concordant in 88% of cases
Ren et al[57], 2021	Prospective molecular reclassification study	KRAS, GNAS, BRAF	108	88.5%	100%	94.3%	KRAS-negative mucinous cysts had alternative BRAF pathway mutations
McCarty et al[44], 2021	Meta-analysis	KRAS, GNAS	785	94%	91%	92.5%	KRA+ GNAS significantly outperformed CEA in mucinous cyst diagnosis
Herranz Pérez et al[58], 2021	Routine practice molecular study	KRAS, GNAS	-	-	-	-	Feasibility and utility confirmed in real-world setting
Pflüger et al[61], 2023	Meta-analysis (42 studies)	TP53, SMAD4, CDKN2A, VHL	666	9%-42%	95%-99%	69.5%	High specificity for HGD; VHL for SCA discrimination
Hata et al[74], 2023	Prospective epigenetic biomarker study	TBX15, SOX17 methylation	70	69.6%	90%	79.8%	Methylation identified HGD in IPMNs
Nikiforova et al[77], 2023	PancreaSeq GC validation (DNA/RNA NGS)	74-gene panel + CEACAM5 mRNA	185	95% (precursor), 82% (HGD)	100%	97.5%	PancreaSeq GC outperformed imaging/cytology in neoplasia detection
Paniccia et al[78], 2023	Multicenter real-time NGS registry	PancreaSeq 22-gene panel	1933	93%	95%	94%	NGS with cytology guided clinical decisions
Hu et al[68], 2024	Review on progression markers	KRAS, GNAS (prognostic)	-	-	-	-	GNAS may be linked to improved recurrence-free survival
Belfrage et al[64], 2024	Prospective diagnostic accuracy study	50-gene NGS, KRAS, GNAS, TP53 + CEA	97	78% (combo)	87%	82.5%	NGS + CEA improved classification and influenced surgical decisions

CEA: Carcinoembryonic antigen; EUS-FNA: Endoscopic ultrasound-guided fine-needle aspiration; AI: Artificial Intelligence; Mol: Molecular; PANDA: Pancreatic cyst DNA analysis; LOH: Loss of heterozygosity; MCN: Mucinous cystic neoplasms; IPMN: Intraductal papillary mucinous neoplasms; IMP: Integrated molecular pathology; NGS: Next-generation sequencing; HGD: High-grade dysplasia; AGA: American Gastroenterological Association; GC: Genomic classifier.

Table 3 Diagnostic ability of various cystic fluid biomarkers

Molecular marker	Diagnostic ability of mucinous cysts	AUC for mucinous cysts diagnosis (range)	SENS for mucinous cysts diagnosis (range)	SPEC for mucinous cysts diagnosis (range)	Diagnostic ability discriminating malignant from non -malignant cysts	Simplicity of use/availability
Cystic CEA	Moderate	0.633-0924	48%-95.4%	82%-98%	-	Moderate
Cystic glucose	Moderate	0.870-0980	89%-95%	78%-95.1%	-	Good
Cystic amylase	-	-	-	-	Inadequate	Moderate
KRAS	Moderate	-	61%	99%	Inadequate	Inadequate
GNAS	Moderate	-	39%-90%	100%	Inadequate	Inadequate
KRAS + GNAS	Moderate	-	79%	98%	Inadequate	Inadequate

CEA: Carcinoembryonic antigen; AUC: Area under the curve; SENS: Sensitivity; SPEC: Specificity.